Methods and arrangements to process comments

ABSTRACT

Described herein are embodiments for managing comments in a program code file. A system may select program code and compile it to an intermediary code. The system may compare the intermediary code to a library of intermediary code snippets associated with comments. Based on the comparison, a system may recognize the code to be obsolete. In some embodiments, a system may generate one or more recommendations to update a code. Based on received feedback regarding a recommendation, a system may accordingly update a code.

BACKGROUND

Programmers may create notes about code in the form of comments. Detailsin code comments may improve human understanding of code, such as byexplaining context related to the code or how the code works. Codecomments may include pseudo-code, natural language, or formatting thatis ignored by code compilers. Some tools may analyze a programmer's codeand generate comments automatically. Some tools may gather comments froma code and create documentation about the code from the comments.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-C depict exemplary user interfaces relating to the managementof code comments.

FIG. 2 is an exemplary block diagram illustrating an architecturesuitable for use with various embodiments.

FIG. 3 is an exemplary block diagram illustrating a model trainingarchitecture suitable for use with various embodiments.

FIG. 4 is a data flow diagram depicting exemplary data flows formanaging code comments.

FIG. 5 is a block diagram depicting an exemplary computing devicesuitable for use with exemplary embodiments.

FIG. 6 is a block diagram illustrating an exemplary system architecturesuitable for use with various embodiments.

FIG. 7 is a block diagram depicting an exemplary communicationarchitecture.

FIGS. 6-8 is a block diagram depicting an exemplary computer such as aserver, data storage device, or client device.

FIGS. 9-10 depict embodiments of a storage medium and a computingplatform of embodiments described herein.

DETAILED DESCRIPTION OF EMBODIMENTS

Programmers may use comments in code to keep clear records of thecontext of a code and/or how the code works. However, each time the codeis changed, the comments may become outdated. The programmer may need tomanually review the code for outdated comments and update them to matchchanges to the code. A code review may be a tedious and/or slow process,and programmers may be discouraged from properly updating code comments.In some cases, codes may be managed across platforms and codinglanguages. Keeping comments updated, then, may require a high level ofskill that not all programmers possess. Even if a programmer tries toupdate comments, the code may be complex. The programmer may makemistakes. In any of these cases, the resulting mismatch between commentsand code may be confusing and/or misleading.

Aspects disclosed herein provide solutions for one or more of thepreceding weaknesses. A system may select program code and compile it toan intermediate language code. An intermediate stage code may be codecompiled in an intermediate stage, for example, between program languageand computer language. The system may compare the intermediate languagecode to a library of intermediate language code snippets associated withcomments. Using the intermediate language code may enable the system toeasily adapt to codes based on different platforms and/or languages.

Based on the comparison, the system may select one or more candidatecomments as potentially being relevant to the selected program code. Thesystem may present the comments as options to a user and receivefeedback for the options. Based on the feedback, the system may insertthe comments into the program code. The comments may be inserted intothe code in accordance with the platform and/or language of the originalprogram code.

In some cases, the system may compare the intermediate language code tocode snippets in the library by checking for an exact match, calculatinga Levenstein distance, or using a model. A model may be based on codefrom an internal code bank or on an external code bank, such as athird-party and/or open source code bank.

In some cases, the system may determine that a comment previouslyassociated with a program code does not match determined candidatecomments. Thus, the system may determine that a program's code isoutdated and/or obsolete. The system may present options to a user fornew comments, and, based on receiving user feedback, replace theobsolete comments with updated comments.

Accordingly, one or more advantages may be provided. Basing commentanalysis on code compiled to an intermediary stage may enable systems toanalyze code from a variety sources and/or source languages. Anembodiment may make recommendations of comment updates for a codesegment based on analysis of code from a plurality of sources and/orsource languages, increasing likelihood of the relevance ofrecommendations. Presentation of, reception of selection of, and/orintegration of recommendations may decrease the time and/or stepsrequired for a programmer to maintain up-to-date comments in a code,increasing the relevancy and/or readability of code.

Computers may thus be enabled by embodiments described herein to managecomments in code via new methods, for example, by analysis of codecompiled to an intermediary stage. Computers may be enabled in apractical application to determine recommendations for comment updatesin a code based on code segments from a plurality of code sources and/orlanguages. Accordingly, additional and useful functionality may be addedto one or more computer devices by embodiments described herein.

In many embodiments, one or more of the components described herein maybe implemented as a set of rules that improve computer-relatedtechnology by allowing a function not previously performable by acomputer that enables an improved technological result to be achieved.For example, automatically detecting an obsolete comment in a codeand/or providing comment recommendations for a code may be improvedtechnological results. In further examples, automatic selection may bean improved technological result, and/or integration of a commentrecommendation automatically or based on a selection of therecommendation may be an improved technological result.

With general reference to notations and nomenclature used herein, one ormore portions of the detailed description which follows may be presentedin terms of program procedures executed on a computer or network ofcomputers. These procedural descriptions and representations are used bythose skilled in the art to most effectively convey the substances oftheir work to others skilled in the art. A procedure is here, andgenerally, conceived to be a self-consistent sequence of operationsleading to a desired result. These operations are those requiringphysical manipulations of physical quantities. Usually, though notnecessarily, these quantities take the form of electrical, magnetic, oroptical signals capable of being stored, transferred, combined,compared, and otherwise manipulated. It proves convenient at times,principally for reasons of common usage, to refer to these signals asbits, values, elements, symbols, characters, terms, numbers, or thelike. It should be noted, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to those quantities.

Further, these manipulations are often referred to in terms, such asadding or comparing, which are commonly associated with mentaloperations performed by a human operator. However, no such capability ofa human operator is necessary, or desirable in most cases, in any of theoperations described herein that form part of one or more embodiments.Rather, these operations are machine operations integrated in practicalapplications, e.g., to identify useful comments for intermediate codesegments and/or to identify and/or replace obsolete comments associatedwith intermediate code segments.

Useful machines for performing operations of various embodiments mayinclude general purpose digital computers as selectively activated orconfigured by a computer program stored within that is written inaccordance with the teachings herein to form specific purpose machines,which may or may not include apparatuses, such as application specificintegrated circuits (ASICs), specially constructed to implementembodiments described herein. Various embodiments also relate toapparatus or systems for performing these operations in a practicalapplication to accomplish specific results or intermediate operationsrelated to obtaining specific results. These apparatuses may bespecially constructed to implement embodiments described herein. Therequired structure(s) for a variety of these machines to implementembodiments described herein will be apparent from the descriptiongiven.

Reference is now made to the drawings, wherein like reference numeralsare used to refer to like elements throughout. In the followingdescription, for purposes of explanation, numerous specific details areset forth in order to provide a thorough understanding thereof. However,the novel embodiments can be practiced without these specific details.In other instances, well known structures and devices are shown in blockdiagram form to facilitate a description thereof. The intention is tocover all modifications, equivalents, and alternatives consistent withthe claimed subject matter.

In the Figures and the accompanying description, the designations “a”and “b” and “c” (and similar designators) are intended to be variablesrepresenting any positive integer. Thus, for example, if animplementation sets a value for a=5, then a complete set of components122 illustrated as components 122-1 through 122-a may include components122-1, 122-2, 122-3, 122-4, and 122-5. Embodiments are not limited inthis context.

FIG. 1A-C illustrate exemplary user interfaces according to one or moreembodiments described herein. Embodiments are not limited in thiscontext.

A system may generate a graphical user interface (GUI) associated withthe input of text in one or more languages. In some embodiments, a GUImay be presented via a processor with an integrated display driver or aprocessor coupled with a display driver and via a display device. Thedisplay device, such as a screen or monitor, may couple to a computingdevice containing logic circuitry of a comment manager system. In manyembodiments, a GUI may include an integrated development environment(IDE). The IDE may contain at least one of a code editor, a debugger, acompiler, or a comment manager. Via the comment manager, the IDE may beconfigured to remove obsolete comments from a code, insert new commentsin a code, and/or update comments in a code. Logic circuitry may referto the hardware or the hardware and code that implements one or morelogical functions, as described herein.

For the sake of simplicity, the present description will refer toexamples of input text being programming code and the respectivelanguage being a programming language. However, it will be appreciatedthat embodiments may be applied to input text comprising naturallanguage, or another text form, and that languages may comprise naturallanguages, machine languages, or other known languages.

FIG. 1A illustrates an exemplary GUI in the form of user interface 101.In some embodiments, a user interface 101 may be associated with acomment manager system. A user interface 101 may include a programmingenvironment. In many embodiments, a programming environment may comprisean IDE for input of commands to process a code, such as runtimeenvironment 102. For example, runtime environment 102 is illustrated asincluding received commands to import a function “printdoub,” save avariable “num” as 5, and run the function printdoub on the num variable.Commands may be processed based on received input, for example. In somecases, a runtime environment 102 may receive code and/or text to analyzefor comment content. In some embodiments, the user interface 101 mayreceive text and/or commands exclusively through a runtime environment102. In some embodiments, a user interface 101 may additionally, oralternatively, receive text and/or code in a separate workspace, such asworkspace 103.

As illustrated with respect to workspace 103, code may include textdesignated as comments. Comments may be parts of code written to help auser determine the context and/or function of a code or a part of acode. Comments may pertain to a code related to a file, such as a headercomment 104-1 (in lines 1 through 4 of the illustrated code), to a codesection such as code section 105-1 (for example, lines 7-9 of the code),or to a code segment, such as comment 106-1 (line 8 of the code).

However, code may lack comments relating to a part of a code, orcomments may be outdated. For example, code section 105-1 may be missinga comment, and comment 106-1 may be outdated, obsolete, and/or otherwiseincorrect.

One or more embodiments may insert and/or update comments relating to acode. An instruction to begin analysis of a code and/or comment may bereceived via a button on a user interface, such as via Insert Commentsbutton 107 and/or Update Comments button 108, or via an entered textcommand, such as commands 109 (for example, lines 4-5 in runtimeenvironment 102). Various command entry points, such as buttons 107 and108 and runtime environment 102, may be used to access the same ordifferent functionality of a comment manager. For example, an UpdateComments button 108 may be used to receive an instruction including anupdating of outdated comments in addition to inserting new and/ordeleting old comments, or the functionality may be limited to updatingtext in existing comments. Aspects are illustrated in FIG. 1A by way ofexample and do not limit this context.

Specifically, embodiments may compile a code or a part of a code to anintermediate language. If a text is not a code, systems may otherwisecompile a text and/or file to an intermediate language interpretation.The compiled intermediate code may be compared to intermediate codesegments in a library, wherein the intermediate code segments areassociated with comments. A library may include intermediate codesegments from a local databank, from user entry, or for an externalcoupled database. For example, a library may include code derived froman open-source platform managed by a third party. Sources included in alibrary may be set as a default or adjusted through a user interface,such as via a settings selection menu 110.

Based on the comparison, comments associated with the compiledintermediate code may be compared to the comments associated with thelibrary intermediate code segments. Based on one or both of the codecomparison and comment comparison, embodiments may generate recommendedupdates to comments associated with the original program code.

Recommended updates to comments may be displayed via a user interface,such as user interface 111 of FIG. 1B. A user interface 111 may includesome, all, or none of the characteristics of a user interface 101. Forexample, a user interface may be a user interface 101, a separate page,a pop-up view, or other display.

One or more recommendation menus, such as code insertion options menu112 and code update options menu 113, may be displayed on a userinterface 111. Recommendation menus may be displayed in association withall or part of a program code, such as code 114. For example,recommendation menus may be associated with code via arrows,highlighting, or other indicators of a code section or location within acode, with a display of a code preview in the recommendation menu, orother method of visualizing the connection. Recommendation menus may bedisplayed concurrently for different parts of code or concurrently. Forexample, a recommendation menu many be presented with relation to oneidentified issue, and when a response is received to resolve the issue,the recommendation menu may be updated and/or replaced by another for asubsequent issue. In some embodiments, multiple identified issues may bepresented together in a single recommendation menu.

Recommendation menus may display one or more recommendations to updatecomments based on a code and/or comment analysis. For example, codeinsertion options menu 112 includes recommendations 115-1, 115-2, and115-3, and code update options menu 113 includes recommendations 116-1,116-2, and 116-3. Recommendations may include comments of variousformats or the same format. For example, recommendation 115-1 may be acomment formatted to annotate a single line or minor component of acode, whereas recommendation 115-2 may be an option formatted to enablerecognition of a distinct section in the code. Recommendations mayinclude an option to forego any of the options, such as inrecommendations 115-3 and 116-3. A user interface 111 may receiveinstructions to present alternative and/or recalculated recommendationsvia a recommendation option, such as via refresh buttons 115-4 and116-4.

Recommendation menus may receive indications of selection of one or moreoptions via a selection of a displayed recommendation, such as by aclickable button, a dropdown menu, a checkbox, or other selectionmethod. Based on the received indication(s), embodiments may update oneor more comments of a program code, as illustrated in FIG. 1C. Updatinga comment may include inserting a comment and/or deleting a comment. Theupdate of a comment may occur in real-time, near real-time, or after anumber of instructions have been received via recommendation menus. Forexample, updates may not be made to a code's comments until some or allidentified issues have been resolved via recommendation selections.

In some embodiments, comments may be updated without a receivedselection. For example, embodiments may update one or more commentsautomatically according to the most-likely recommendation option. Insome embodiments, comments may be updated automatically based on theupdate being designated a non-substantive and/or bibliographic update.For example, embodiments may update a header comment with details aboutrecent activity relating to the code and/or comments, such as in headercomment 104-2.

Additionally, or alternatively, comments may be updated based onreceived feedback. For example, a portion of code 105-1 may have beenidentified by a comment manager as lacking a descriptive comment. A codeinsertion options menu 112 may have been accordingly presented, and aselection of recommendation 115-2 received. Based on the receipt of theselection, a comment manager may insert comment 117-1. The formatting ofcomment 117-1 may indicate portion of code 105-1 as a defined section ofthe code 105-2.

In another example, a code manager may recognize comment 106-1 as beingpotentially outdated and/or obsolete. For example, library intermediatecode segments corresponding to a multiplication by two may be associatedwith comments containing the word “double” instead of “triple.” Based onthe recognition, a code update options menu 113 may be presented and aselection of a recommendation 116-1 subsequently received. Accordingly,the comment 106-1 may be updated to comment 106-2, incorporating thechange indicated by the recommendation 116-1. In some embodiments, arecommendation may include an option to delete a potentially obsoletecode. Accordingly, an update to a comment may comprise a commentaddition and/or a comment deletion.

In some embodiments, comments may be updated in a code based on aconfidence level associated with the comment being above a threshold. Aconfidence-based update may not require receipt of feedback via arecommendation menu. For example, a comment 117-2 may have been insertedinto the code based on a high confidence level. In another example, acomment may be deleted automatically based on a high confidence levelindicating that the comment is likely obsolete. Confidence levels may bebased on calculated differentiation of a code from an expected codeidentified from a library and/or constructed via use of a machinelearning model.

A code file may be saved automatically throughout an updated process inthe same or a new version, for example, after each update.Alternatively, changes may not be immediately saved. A notification ofthe completion of a code and/or comment analysis may be displayed, suchas in printed response 118. Alternatively, or additionally,notifications may be presented via other methods, for example, in acomment update, such as in header comment 104-2, a pop-up notification,or a message otherwise displayed or sent.

FIG. 2 illustrates an exemplary block diagram according to one or moreembodiments described herein. Components of architecture 200 may beimplemented on at least one apparatus, transitory and/or non-transitorystorage medium containing instructions, logic circuitry, or combinationthereof, such as discussed with respect to FIGS. 5-6. Logic circuitry,refers to the hardware or the hardware and code that implements one ormore logical functions, as described herein. Components of architecture200 may be coupled via a wired connection, a wireless connection, or acombination thereof, and may be implemented in a single device or acrossmultiple devices. Embodiments are not limited in this context.

At least one file 201-n may contain compilable material. In manyembodiments, files may contain program code, wherein program code refersto code in a human-understandable programming language. A file 201-n maycontain one or more comments comprising text to be ignored by acompiler. Files such as file 201-n may be stored in a local datastore,remote datastore, or a combination thereof.

A user interface 203 may receive and/or display program code 202 fromone or more files 201-n. The user interface 203 may be a part of orotherwise communicatively coupled to processing logic, such as in alaptop computer, desktop computer, mobile device, or server. The userinterface 203 to receive input, such as via a keyboard and/or mouse.Furthermore, the user interface 203 may visually display information,such as aspects of a file 201-n and/or a comment manager. Furthermore,the user interface 203 may display comments associated with the programcode 202.

The user interface 203 may be coupled to a comment manager 204. Invarious embodiments, the comment manager 204 may be embodied on one ormore computer-readable storage media, for example, in association with auser device and/or server. In many embodiments, a comment manager 204may be implemented in logic circuitry comprising one or more circuits.

Specifically, a comment manager 204 may receive a comment analysisrequest 205 at a program code identifier 206. A comment analysis request205 may be received based on input received at the user interface 203.In some embodiments, a request may comprise a direct instruction, suchas via one of buttons 107 and 108 or an entered command 109.

Alternatively, or additionally, a request may comprise an inferredinstruction. For example, settings for a comment manager 204 mayinstruct partial or full analysis of comments to be performed based on atrigger at the user interface or in a file 201-n. For example, thesaving of a file 201-n may indicate an updated code, and a userinterface 203 may accordingly send a comment analysis request 205 to acomment manager 204. In some embodiments, a comment manager 204 and/or aprogram code identifier 206 may retrieve all of or part of a programcode 202 from a file 201-n based on receiving a comment analysis request205, as part of a comment analysis request 205, or in conjunction with acomment analysis request 205.

A program code identifier 206 may identify all or part of a program code202 as a program code segment to be analyzed. In many embodiments, aprogram code identifier 206 may identify segments of a program code inconjunction with and/or based on comments associated with parts of orall of the program code. The segment of program code together with theassociated comments may be sent as a program code segment 207 to a codeassembler 208. In other embodiments, a segment of program code may besent as a program code segment without any associated comments. In someembodiments, a program code segment 207 may include one or moreidentifiers. Identifiers may indicate a program language, a user and/orentity associated with the code, or other indications of the context ofthe program code.

A code assembler 208 may receive a program code segment 207 and compilethe program code segment 207 to an intermediate language. Variousembodiments may include one or more code assemblers 208 capableindividually or together of compiling code from a plurality of sourcelanguages to a common intermediate code language. In this way,embodiments may enable the management of program codes from across aplurality of platforms. Compiled intermediate code may be associatedwith the same respective comments and identifiers as program codesegments 207 and send as intermediary code segment 209 to anintermediary code comparer 210.

An intermediary code comparer 210 may use the intermediary code segment209 to determine whether a corresponding program code 202 requiresupdated comments. Specifically, an intermediary code comparer mayreceive and/or identify a segment of test code in the intermediarylanguage. In some embodiments, the test code may be identified using atleast one model 211-n. The test code may be selected and/or constructedbased on similarity to the intermediary code in the intermediary codesegment 209.

A model 211-n may comprise a database, a statistical model, a machinelearning model, or a combination thereof. In some embodiments, asimilarity between intermediary code segments, such as between anintermediary code segment 209 and a test code, may be determined using aLevenshtein distance metric. For example, a model 211-n may includeand/or otherwise employ a Levenshtein distance metric.

The intermediary code comparer 210 may retrieve and/or receive a testcode from a datastore of code segments. For example, a library 213 maybe a datastore including a data structure configured to store commentsfrom one or more different source program and/or training codes, alongwith associations identifying corresponding intermediate code segmentswith the source codes. A library 213 may comprise at least one codesegment 214-n. A code segment 214-n in a library may be stored locallyto a library 213 or be stored remotely. In some embodiments, aspects ofa library 213, which may include a code segment 214-n, may include datamanaged by third-party entities. For example, a library 213 may includeat least one code segment 214-n from an open-source programming system.Inclusion of code segments from various sources may benefit a system byincreasing a likelihood that comments associated with a code arerelevant across users and platforms.

In many embodiments, code segments may be repeated in a library 213. Forexample, two identical or substantially similar code segments 214-n maybe included in a library 213 based on their inclusion in an open sourceproject. Repeated, identical, and/or substantially similar code segmentsmay be identified by a model, Levenshtein distance under a thresholdvalue, or direct match as described with respect to other componentsdescribed herein.

Identical or substantially similar code segments 214-n may be associatedwith the same or with different comments. In many embodiments, identicalor substantially similar code segments may be associated with and/orlinked to each other in a library. As a result, each of the commentsassociated with any of the linked code segments may be associated withall the linked code segments. In some embodiments, repeated, identical,and/or substantially similar comments code segments may be merged orotherwise represented by a single entry in a library 213, wherein allthe comments of the individual code segments associated therewith areassociated with the single entry. Likewise, repeated and/orsubstantially similar comments may be represented by a common listing.

In some embodiments, one or more counter values may be associated withthe library entry and/or the comments associated therewith. For example,a counter value of twenty may be associated with a code segment 214-n iftwenty repetitions of the code segment were identified across thesources for the library 213. In this example, if four of the repetitionsof the code segment had contained the same comment A, then the codesegment 214-n may be associated with the comment A with a relatedcounter of four. In this way, the storage requirement of a library maybe decreased while context is kept relating to the popularity of a codesegment and/or comment across multiple sources.

In some embodiments, an intermediary code comparer 210 may use anintermediary code segment 212, which may be all or part of anintermediary code segment 212 including a code segment in anintermediary language, to access code segments a library 213. Forexample, an intermediary code comparer 210 may identify a code segment214-n in a library 213 based on an exact match to an intermediary codesegment 212. In some embodiments, a code segment 214-n may be identifiedbased on a minimized Levenshtein distance between one or more codesegments in the library 213. In some embodiments, a code segment 214-nmay be identified at the intermediary code comparer 210 based onsimilarity to a test code identified by a model 211-n. The model 211-ninformed by one or more code segments 214-n from a library 213, asdescribed in greater detail with respect to FIG. 3. At least one codesegment 214-n identified as a match to intermediary code segment 212 maybe sent to or retrieved by the intermediary code comparer 210 as alibrary code segment 215. Comments associated with the code segment214-n may be sent in association with and/or as a part of library codesegment 215.

In many embodiments, an intermediary code comparer 210 may use a librarycode segment 215 determined to correspond with an intermediary codesegment 212 and/or an intermediary code segment 209 as a test codesegment. The intermediary code comparer 210 may compare the intermediarycode segment 209 with the test code segment as described above.

A library 213 may be used, in some embodiments, to train one or more ofthe models employed by the intermediary code comparer 210. For example,a model trainer 216 may retrieve a library code segment 215 comprising acode segment 214-n and one or more associated comments from a library213. The model trainer 216 may generate, develop, and/or update at leastone model based on the library code segment 215. In many embodiments, amodel trainer 216 may retrieve a plurality of library code segments 215from a library 213 and accordingly train one or more models. Models mayinclude neural networks, distance measurements, and/or other constructsuseful for recognizing the relationships between different library codesegments, between code segments and associated comments in a librarycode segment, and/or between comments associated with different librarycode segments. A model trainer may provide at least one model 217 foruse by an intermediary code comparer 210. For example, a model 211-n maybe a model 217.

In some embodiments, an intermediary code comparer 210 may determine astatus of an intermediary code segment 209 based on one or morecomparisons between the intermediary code segment 209 and the test code.For example, measures of similarity between the intermediary codesegment and the test code and/or between the comments associated witheach may be used to determine if comments associated with anintermediary code segment 209 match comments associated with arespective test code. A lack of a match or a low confidence match mayindicate that a comment is outdated and/or obsolete.

Based on the determination of similarity and/or deviation between theintermediary code segment 209 with the test code segment, theintermediary code comparer 210 may generate a comparison result 218. Thecomparison result 218 may include measures of similarity between theintermediary code segment and the test code and/or between the commentsassociated with each. For example, a comparison result 218 may include aLevenshtein distance of 0 indicating an exact match between a librarycode segment 215 and an intermediary code segment 209. In anotherexample, a comparison result 218 may include a Levenshtein distance of 1indicating a difference in one character between a library code segment215 and an intermediary code segment 209. Furthermore, the comparisonresult 218 may include measures of similarities between commentsassociated with the intermediary code segment 209 and the library codesegment 215. For example, the comparison result may include similarityand/or deviation scores for each multiple library code segment 215comment associated with a single comment intermediary code segment 209comment in a many to one ratio. Comments or pointers to the librarylocation of the comments may be included in association with theirrespective similarity score. If the intermediary code comparer 210 hasdetermined a status of a comment, the status determination may beincluded in the comparison result 218.

A response generator 219 may retrieve and/or receive a comparison result218 from an intermediary code comparer 210. Based on the comparisonresult 218, the response generator 219 may send a comment status alert220 and/or at least one comment suggestion 221.

A comment status alert 220 may include an indication of whether aspecified comment and/or a section in a program code may need to beinserted, updated, or otherwise altered. A comment status alert 220 mayinclude a notification, an indication, a recommendation menuconfiguration, and/or other flag useful for enabling a user interface203 to display a communication related to the comments of a file 201-n.In many embodiments, a comment status alert 220 may contain an indicatorof at least one file 201-n, a code section therein, or a comment thereinrelated to a comparison result 218.

A comment suggestion 221 may contain one or more comments related to acomparison result 218. If the comparison result 218 included pointers tolibrary locations of comments, the response generator 219 may retrieveone or more comments from the library 213 based on the pointer and theninclude them in the comment suggestion 221. In some embodiments, allcomments indicated by a comparison result 218 may be included in acomment suggestion 221. In some embodiments, only some of the commentsassociated with a comparison result 218 may be included in a commentsuggestion 221. For example, a comment suggestion 221 may include onlythe several comments with the highest associated similarity scores.

Comment status alerts 220 and comment suggestions 221 may be separate orunified packages. For example, a unified package may include a commentstatus alert 220 indicating line 8 of the program code of workspace 103as requiring an update and a comment suggestion 221 includingrecommendations 116-1, 116-2, and 116-3. The unified package may be usedto generate a code update options menu 113.

A response generator 219 may send a comment status alert 220 and/or acomment suggestion 221 to a user interface 203. The user interface 203may display a notification, menu, and/or other message related to one ormore aspects received from a response generator 219. For example, theuser interface 203 may display a code update options menu 113.

The user interface 203 may receive feedback based on the comment statusalert 220 and/or comment suggestion 221. For example, the user interface203 may receive via a mouse click a selection of a recommendation 116-1of a code update options menu 113 based on a comment suggestion 221. Insome embodiments, feedback may be received via a keyboard, such as via atyped command in runtime environment 102. Feedback may be sent from theuser interface 203 to the comment manager 204 as a suggestion selection222. In some embodiments, suggestion selection 222 may be received by aresponse generator 219.

Based on the suggestion selection 222, the response generator 219 maysend another comment status alert 220 and/or another comment suggestion221. For example, if the suggestion selection 222 includes a selectionof a recommendation relating to a recommendation menu, a new commentstatus alert 220 and a new comment suggestion 221 may be sent so thatthe user interface 203 may update the recommendation menu to address anew section of the code. In another example, if a suggestion selection222 includes an indication of the selection of a refresh button, such asrefresh button 115-4, a new comment suggestion 221 may be sent without anew comment status alert 220. This may enable the user interface 203 todisplay new recommendations while limiting the required handoffs ofinformation between components.

In many embodiments, a comment manager 204 may updated a file 201-nbased on a suggestion selection 222. In some embodiments, a responsegenerator 219 may access the file 201-n associated with the comparisonresult 218 and update a program code based on a received suggestionselection 222. The update may be applied to the file 201-n as codeupdate 223. The file 201-n may be automatically saved and/or saved basedon feedback received via the user interface 203. The updated file 201-nmay be displayed via the user interface 203 in real- or near real-time.

FIG. 3 illustrates an exemplary block diagram for training one or moremodels according to one or more embodiments described herein. Forexample, models 211-n may be trained by the methods described withrespect to FIG. 2. Embodiments are not limited in this context.

At least one program code segment 301-n may each contain a code 302-nand at least one comment 303-n. Code 302-n may include all or part ofthe code contained in a file, such as file 201-n. Each comment 303-n maybe associated with some or all the code 302-n. Each program code segment301-n may have code, such as code 302-n, in the same or in differentprogram languages. A comment 303-n in a program code segment 301-n mayhave formatting corresponding to the code 302-n of the program codesegment 301-n.

A code parser 304 may process one or more program code segments 301-n. Acode parser 304 may generate at least one training code segment 305-nbased on a program code segment 301-n. Training code may include code ina source language. Training code may contain comments associated withprogram code. For example, a code parser 304 may divide a program codesegment 301-n into at least one training code segment 305-n.

A code parser 304 may make divisions based on one or more codes 302-n ina program code segment 301-n and/or one or more comments 303-n. Forexample, a code parser 304 may divide a program code segment 301-n intoseveral training code segments 305-n based on the program code segment301-n containing several codes 302-1 . . . 302-n representing sectionsof a program code, such as code section 105-1. Additionally, oralternatively, a code parser 304 may divide a program code segment 301-ninto several training code segments 305-n based on comments 303-1 . . .303-n contained in the program code segment 301-n. For example, the codeparser 304 may divide a program code segment 301-n into segments of codebased on the code 302-1 . . . 302-n's association with comments 303-1 .. . 303-n. A comment 303-n may be used to identify a section of code,such as code 302-n, based on formatting, or a code parser 304 may definea section of code based on a comment 303-n. For example, a code parser304 may define a code section for a training code segment 305-n asincluding line 8 of the code contained in workspace 103, wherein thedefinition is based on the presence of comment 106-1. In someembodiments, a code parser 304 may combine two or more program codesegments 301-n in order to generate a training code segment 305-n.

Each training code segment 305-n may have code, such as code 306-n, inthe same or in different program languages. A comment 307-n in atraining code segment 305-n may have formatting corresponding to thecode 306-n of the training code segment 305-n. A program language of atraining segment 305-n may be the same as or different from acorresponding program segment 301-n. For example, two program codesegments 301-1 and 301-2 may be associated with different programlanguages but used to generate a common training code segment 305-nbased on a comparison of respective comments 303-1 and 303-2 and/orother indicators. In this example, the resulting training code segment305-n may be in one of the two program languages or in a third language.A training code segment 305-n may include one or more indications oftraining languages associated with a corresponding program code segment301-n used in its generation.

Code and/or comments of a program code segment 301-n may be repeated ornot included in a training code segments 305-n. For example, a codeparser 304 may not generate a training code segment 305-n from a programcode segment 301-n which does not contain a comment 303-n.

Each training code segment 305-n may contain one or more sections ofcode 306-n and/or one or more comments 307-n. Code 306-n and comment307-n may be associated with each other in a one-to-one, a one-to-many,or a many-to-one relationship. For example, two program code segments301-1 and 301-2 may contain the same code 302-1 but different comments303-1 and 303-2. In this example, a code parser 304 may combine programcode segments 301-1 and 301-2 into a single training code segment 305-1containing a single code segment 306-1 corresponding to code 302-1, aswell as comments 307-1 and 307-2 corresponding to comments 303-1 and303-2. Each comment 307-n in a training code segment 305-n may be thesame, a copy of, or different than a comment 303-n in a program codesegment 301-n used to generate the training code segment 305-n. Forexample, a code parser 304 may generate a comment 307-n based onmultiple program code segments 301-n by using a model, a library ofsimilar comments, and/or other method.

A compiler 308 may process at least one training code segment 305-n. Inmany embodiments, a compiler 308 may compile a training code segment305-n into an intermediate code segment 309-n. A compiler 308 mayprocess a plurality of training code segments 305-1 . . . 305-n inseries or in parallel to produce a plurality of intermediate codesegments 309-1 . . . 309-n. In some embodiments, an intermediate codesegment 309-n may include one or more indications of association with atleast one training code segment 305-n and/or program code segment 301-nused in its generation.

An intermediate code segment 309-n may include code 310-n associatedwith code 306-n. In many cases, a code 310-n may be a 306-n that hasbeen compiled into an intermediate language. Training code segments305-1 . . . 305-n may be associated with the same or differentprogramming languages. Intermediate code segments 309-1 . . . 309-n may,in many embodiments, be associated with the same intermediate language.Accordingly, a plurality of languages associated with program codes301-1 . . . 301-n may be processed to generate intermediate codesegments 309-1 . . . 309-n in a common intermediate language, enablingcomparison of code functionality across languages rather than comparisonof specific programming language traits.

An intermediate code segment 309-n may include at least one comment311-n. A comment 311-n may be associated with a code 310-n and beassociated with at least one comment 307-n of a respective training codesegment 305-n. In some embodiments, a comment 311-n may be the same as arespective comment 307-n. In other embodiments, a compiler 308 mayprocess a comment 307-n to generate comment 311-n by changing formattingand/or other content to match a generalized comment format of theintermediate language.

A model trainer 312 may use at least one intermediate code segment 309-nto train at least one model 313-n. A model 313-n may be trained torecognize and/or determine aspects of an intermediate code segment 309-nbased on aspects of a corresponding program code segment 301-n.Additionally, or alternatively, a model 313-n may be trained torecognize and/or determine aspects of an intermediate code segment 309-nbased on aspects of a corresponding training code segment 305-n. In someembodiments, a model trainer 312 may be a model trainer 216.

A model 313-n may include a determination of an exact match betweencomments of a program code 301-n, a training segment code 305-n, and anassociated intermediate training code segment 309-n. Alternatively, oradditionally, a model 313-n may determine a distance between respectivecomments. For example, a model 313-n may employ a measure of Levenshteindistance or another string metric for measuring the difference betweensequences. A Levenshtein distance, for example, may measure the numberof character differences between two strings.

In some embodiments, a model 313-n may be trained to recognize theassociation between a code 310-n and a comment 311-n. In someembodiments, a model 313-n may be trained to generate a comment 311-nbased on a code 310-n. Additionally, or alternatively, a model 313-n maybe trained to recognize and/or generate at least one program codesegment 301-n based on an intermediate code segment 309-n. For example,based on code 310-n and/or comment 311-n in at least one intermediatecode segment 309-n, a model 313-n may generate a comment in a programlanguage, such as comment 303-n. A model 313-n may include at least oneneural network, such as a convolutional neural network, a recursiveneural network, a sequence-to-sequence model, or other artificialintelligence model. For example, a neural network may be used toidentify similarity between comments by natural language processing(NLP). Accordingly, a system may determine the similarity of commentsbased on context and semantics.

In many embodiments, a model trainer 312 may train and retrain a model313-n, for example, based on the availability of at least one newprogram code segment 301-n, training code segment 305-n, and/orintermediate code segment 309-n, a received instruction, or anotherindication.

FIG. 4 depicts a flowchart showing an exemplary method for managingcomments. Exemplary logic 400 (such as logic circuitry including, e.g.,processing circuitry and computer executable instructions) is organizedinto various groups of logics (e.g., training logic 402, runtime logic409, comment identification logic 410, comment update logic 413, andobsoletion detection logic 418. In some embodiments, these logic modulesmay be provided on one or more servers, as described with respect toFIG. 6, although it is understood that such a configuration is notrequired. All the modules may be implemented in the same device or maybe distributed across any number of devices. Various combinations ofmodules may be employed on a given device, or the logic of an individualmodule may be performed by different devices. Embodiments are notlimited in this context.

Processing begins at block 401, where logic may receive a request toanalyze comments in association with one or more sets of program code.For example, a request may be a comment analysis request 205. In someembodiments, a request may be an event. For example, a user interface203 may receive entry of program code, such as via a keyboard. An entryof program code may comprise an edit of a program code. When logic hasreceived a sufficient amount of program code to compile the code, arequest event may be triggered. Determination of sufficiency of anamount of received program code may be made based on a number of linesof code received, a number of commands recognized in the code, a save toa file containing the received code, a reception of the beginning of anew section of code, or other method. In some embodiments, a compilablecount of lines may be determined by a preference and/or setting.

From block 401, processing may continue to training logic 402. Traininglogic 402 may be used to train models useful for comment management,such as model 211-n. Training logic 402 may be useful for one or moreaspects of environment 300 and/or a comment manager 204. For example,aspects of training logic 402 may be used by a code parser 304, acompiler 308, and/or a model trainer 312 to train a model 313-n. Inanother example, training logic 402 may be implemented by a modeltrainer 216.

Processing in training logic 402 may begin at block 403 with theidentification of training data. In some embodiments, logic of block 403may be performed by a code parser 304 and identify training datacomprising a training code segment 305-n. In some embodiments, a programcode identifier 206 may function as a code parser 304 and/or otherwiseimplement logic of block 403. Training data may be identified based onan instruction received via a user interface, a determination ofavailability of training data not previously used in training, or otherindication. Training data may be identified from one or more databases,which may be local libraries, remote libraries, or a combinationthereof. In some examples, databases may be managed by a third-party. Invarious embodiments, training data may be identified from an open-sourcecode bank. Training data may be identified as entire contents of codefiles, such as file 201-n, or as a segment or block of code therefrom.For example, training data may be identified as a section of codeincluding a number of lines of code surrounding an associated comment.Training data may be associated with at least one comment.

From block 403, logic may continue to block 404, wherein logic maycompile an intermediary code block. An intermediary code block maycontain code from training data compiled to an intermediary languageand/or compilation stage. For example, an intermediary code block may becode 310-n.

From block 404, processing may proceed to block 405 with the associationof comments with the intermediary code block. Comments associated withthe intermediary code block may include comments originally found intraining data or processed comments. For example, language-specificformatting may be removed in comments associated with intermediary codeblocks. In some embodiments, intermediary code blocks may be associatedwith comments in a datastore, such as library 213. In some embodiments,intermediary code blocks together with associated comments may make upan intermediate code segment 309-n.

Logic at blocks 404 and/or 405 may be performed, in some embodiments, bya code assembler 208 and/or a compiler 308.

Processing may continue from block 405 to block 406. Logic at block 406may train one or more models. Models may be useful for determining thesimilarity of an intermediary code block to intermediary code in alibrary and/or the similarity of comments associated with anintermediary code block to comments associated with intermediary code ina library. Models may include one or more of neural networks, differencemeasures such as a Levenshtein distance, determination of an exactmatch, or other method for analyzing differences between strings. Insome examples, logic at block 406 may be implemented by a model trainer312.

From block 406, processing may proceed to block 407. At block 407, adetermination may be made, for example, by a comment manager 204,whether additional training of a model should be performed. In somecases, determination may be made based on the availability of data whichhas not been previously used to train a model. For example, new datareceived via a keyboard coupled to a user interface, new data availablevia a remote library, or other data received may be available fortraining a model. A determination may be based on receipt of aninstruction to re-enter a training process, in some cases. For example,an instruction may be received via a user interface. In some cases, adetermination may be automatically set, such as, by a time frame. Forexample, a setting may indicate that training should be performedweekly. Based on the determination that additional training is desired,logic may return to block 403, and training logic 402 may repeat withrespect to the same training data, different training data, or acombination thereof.

If a determination has been made that additional training is notimmediately desired for a model, logic may proceed from block 407. Insome embodiments, processing may end. In some embodiments, processingmay proceed to block 408. In some embodiments, processing may end orwait, then receive a new request in block 401. In some embodiments,processing may directly proceed to block 408 from block 401.Accordingly, training and runtime steps of logic may be unified orseparated in various embodiments.

In block 408, a program code block is identified by logic. A programblock code may be the same or different from previously receivedtraining data, and it may include at least some code in a programlanguage. A program code block may or may not have at least one commentassociated with program code. In some embodiments, a program code blockmay be identified based on one or more comments. For example, a programcode block may be defined as a segment of code including a set number oflines of code before and after a comment. In some embodiments, a programcode block may be defined independently of comments. For example, aprogram code block may be defined as a set number of lines of code, aset number of recognized commands, a formatted section of code, or othersegmentation. In some embodiments, logic associated with block 408 maybe performed by a program code identifier 206 and/or a program codesegment 207 may comprise a program code block.

Block 408 may hand off processing to runtime logic 409. In someembodiments, block 408 may be included in runtime logic 409. Runtimelogic 409 may include one or more logic blocks, such as commentidentification logic 410, obsoletion detection logic 418, and/or commentupdate logic 413. Block 408 may, in some embodiments, hand offprocessing to comment identification logic 410.

Comment identification logic 410 may include blocks 411 and 412. Atblock 411, an intermediate code block may be compiled based on theprogram code block identified in block 408. Logic of block 411 may beimplemented by a code assembler 208, as an example. At block 412, adetermination may be made as to whether a match for comments can beidentified based on a library for the intermediary code block of block411. The determination may be made using a model, such as a modeltrained in block 406.

In some embodiments, a model may be used to determine a match in adatabase for the intermediary code block generated by logic of block411. Logic of block 412 may be performed, for example, by anintermediary code comparer 210. The match may be determined based on amodel, such as model 211-n and/or model 313-n. In many embodiments, aselected match may be a code segment 214-n, including a code segment andassociated comments. Based on the successful determination of a matchfor the intermediary code block, logic may identify comments associatedwith the match in the database.

Based on the determination at block 412, logic may continue to commentupdate logic 413. Comment update logic 413 may include one or more logicpieces that can use results of prior comment analysis to present one ormore practical responses.

For example, if logic of block 412 determines a library match for theintermediary code block of logic block 411, and the match is associatedwith comments, then logic may proceed to logic block 414. In someembodiments, a library match may be a library segment 215. In manyembodiments, logic may progress to block 414 in the case that theintermediary code block is not associated with comments. At block 414,logic may generate a suggestion including one or more comments that areassociated with the match. For example, logic of block 414 may beimplemented by a response generator 219 and a suggestion may comprise acomment status alert 220 and/or a comment suggestion 221. Logic at block414 may provide the suggestion for display via a user interface, forexample, user interface 203. It will be understood that steps ofgenerating the suggestion and providing the suggestion for display maycomprise one or multiple logic steps.

Comment update logic 413 may receive a response to the suggestion ofblock 414 at block 415. In some embodiments, a response received atblock 415 may include a suggestion selection 222. Based on the receivedresponse, logic may proceed by inserting a code update into a programcode at block 416. For example, a code update may comprise code update223. In some embodiments, processing may end at this point. In otherembodiments, the inserted code update may comprise new data that may beused to further train models. For example, the comment indicated asselected by the received response, which had previously only beenassociated with the library match for the intermediary code segment, maybe newly associated with the intermediary code segment in the library asa new training code entry. Accordingly, the insertion may be recognizedas a request 205 by logic of block 401 and/or logic of block 407 may betriggered to train a model based on the insertion via training logic402.

If the logic of block 412 does not find a library match for theintermediary code block of block 411, or if the code match does not haveassociated comments known to the library, logic may proceed from block412 to block 417. At block 417, logic may generate a warning. Logic mayfurther provide the warning for display, such as via user interface 203.A warning may comprise a comment status alert 220 or another indicationthat a comment could not be appropriately matched for the program codesegment via an automated process.

In some embodiments, a warning may prompt manual entry of at least onecomment in association with the program code, which may be received bylogic of block 415. In some embodiments, comment update logic 413 mayinterpret the manual entry as a suggestion selection 222. For example,the entry may be inserted into the code as a code update via logic ofblock 416. In some embodiments, processing may end at this point. Inother embodiments, the inserted code update may comprise new data thatmay be used to further train models. Accordingly, the insertion may berecognized as a request 205 by logic of block 401 and/or logic of block407 may be triggered to train a model based on the insertion viatraining logic 402.

In some embodiments, logic of block 412 may determine that there is alibrary match for the intermediary code block of logic block 411 withassociated comments, wherein the intermediary code block is associatedwith comments. In this case, logic may move from block 412 to obsoletiondetection logic 418. Obsoletion detection logic 418 may determinewhether a comment associated with an intermediary code segment matchesan expected comment for the intermediary code segment. The lack of amatch may indicate that the comment is outdated and/or obsolete. Aspectsof obsoletion detection logic 418 may be performed, for example, by anintermediary code comparer 210.

In particular, logic may progress from block 412 to block 419 inobsoletion detection logic 418. In block 419, a comment associated withthe library match for the intermediary code block may be compared to arespective comment associated with the program code block. Based on thedetermination of the match of the intermediary code block with thematched code block in the library, the comment associated with thelibrary match may be determined to be an expected comment for theintermediary code block and/or respective program code block. In someembodiments, the expected comment may be compared to the actualrespective comment associated with the intermediary code block and/orprogram code block. Comparison may be made using at least one model,such as model 211-n and/or model 313-n, a distance measure, a NLPanalysis, or other method useful for comparing string content, context,and/or meaning. Comparison measures may be quantified in one or morecomparison scores.

Logic may continue from block 419 to block 420, at which point adetermination may be made as to whether the expected comments and therespective comments of the program and/or intermediary code block match.In many cases, a match may be determined by a comparison score beingabove a threshold and/or a deviation score being below a threshold.

A determination that the comments of the intermediary and/or programcode blocks do not match expected comments may cause processing toprogress from block 419 to block 414. At block 414, a suggestion may begenerated based on previous processing and provided, such as via a userinterface 203. A suggestion may comprise a warning that at least part ofa code may be obsolete, and the suggestion may contain a reference tothe part of the code for which comments did not match expected comments.In some embodiments, a suggestion may include one or more expectedcomments, for example, as a recommended replacement for the potentiallyobsolete comments of the respective program code.

Processing may continue to block 415 based on receiving a responseregarding the suggestion of block 414. As explained above, a responsereceived in block 415 may be used to update a program code block inblock 416 and/or initiate a new training phase via training logic 402.

In some embodiments, a notification or indication may be generated atlogic block 421 based on determination of matches between the commentsof program and/or intermediary code blocks and expected comments. Forexample, a confirmation of a calculated likelihood that code is updatedmay be provided via a user interface 203. In many embodiments,processing may end after block 420.

FIG. 5 illustrates an embodiment of an exemplary computing architecture500 that may be suitable for implementing various embodiments aspreviously described such as the client device 602, data storage device618, and or the server 628 shown in FIG. 6. In various embodiments, thecomputing architecture 500 may comprise or be implemented as part of anelectronic device. In some embodiments, the computing architecture 500may be representative, for example, of one or more component describedherein. In some embodiments, computing architecture 500 may berepresentative, for example, of a computing device that implements orutilizes one or more of user interface 203, comment manager 204, codeparser 304, compiler 308, model trainer 312, and/or one or moretechniques described herein. Embodiments are not limited in thiscontext.

As used in this application, the terms “system” and “component” and“module” are intended to refer to a computer-related entity, eitherhardware, a combination of hardware and software, software, or softwarein execution, examples of which are provided by the exemplary computingarchitecture 500. For example, a component can be, but is not limited tobeing, a process running on a processor, a processor, a hard disk drive,multiple storage drives (of optical and/or magnetic storage medium), anobject, an executable, a thread of execution, a program, and/or acomputer. By way of illustration, both an application running on aserver and the server can be a component. One or more components canreside within a process and/or thread of execution, and a component canbe localized on one computer and/or distributed between two or morecomputers. Further, components may be communicatively coupled to eachother by various types of communications media to coordinate operations.The coordination may involve the uni-directional or bi-directionalexchange of information. For instance, the components may communicateinformation in the form of signals communicated over the communicationsmedia. The information can be implemented as signals allocated tovarious signal lines. In such allocations, each message is a signal.Further embodiments, however, may alternatively employ data messages.Such data messages may be sent across various connections. Exemplaryconnections include parallel interfaces, serial interfaces, and businterfaces.

The computing architecture 500 includes various common computingelements, such as one or more processors, multi-core processors,co-processors, memory units, chipsets, controllers, peripherals,interfaces, oscillators, timing devices, video cards, audio cards,multimedia input/output (I/O) components, power supplies, and so forth.The embodiments, however, are not limited to implementation by thecomputing architecture 500.

As shown in FIG. 5, the computing architecture 500 comprises aprocessing unit 504, a system memory 506 and a chipset and bus 508. Theprocessing unit 504 can be any of various commercially availableprocessors, including without limitation an AMD® Athlon®, Duron® andOpteron® processors; ARM® application, embedded and secure processors;IBM® and Motorola® DragonBall® and PowerPC® processors; IBM and Sony®Cell processors; Intel® Celeron®, Core (2) Duo®, Itanium®, Pentium®,Xeon®, and XScale® processors; and similar processors. Dualmicroprocessors, multi-core processors, and other multi processorarchitectures may also be employed as the processing unit 504.

The chipset and bus 508 provides an interface for system componentsincluding, but not limited to, the system memory 506 to the processingunit 504. The chipset and bus 508 can include any of several types ofbus structure that may further interconnect to a memory bus (with orwithout a memory controller), a peripheral bus, and a local bus usingany of a variety of commercially available bus architectures. Interfaceadapters may connect to the chipset and bus 508 via a slot architecture.Example slot architectures may include without limitation AcceleratedGraphics Port (AGP), Card Bus, (Extended) Industry Standard Architecture((E)ISA), Micro Channel Architecture (MCA), NuBus, Peripheral ComponentInterconnect (Extended) (PCI(X)), PCI Express, Personal Computer MemoryCard International Association (PCMCIA), and the like.

The system memory 506 may include various types of computer-readablestorage media such as non-transitory computer-readable storage media inthe form of one or more higher speed memory units, such as read-onlymemory (ROM), random-access memory (RAM), dynamic RAM (DRAM),Double-Data-Rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM(SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM),electrically erasable programmable ROM (EEPROM), flash memory (e.g., oneor more flash arrays), polymer memory such as ferroelectric polymermemory, ovonic memory, phase change or ferroelectric memory,silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic or opticalcards, an array of devices such as Redundant Array of Independent Disks(RAID) drives, solid state memory devices (e.g., USB memory, solid statedrives (SSD) and any other type of storage media suitable for storinginformation. In the illustrated embodiment shown in FIG. 5, the systemmemory 506 can include non-volatile memory 510 and/or volatile memory512. In some embodiments, system memory 506 may include main memory. Abasic input/output system (BIOS) can be stored in the non-volatilememory 510.

The computer 502 may include various types of computer-readable storagemedia in the form of one or more lower speed memory units, including aninternal (or external) hard disk drive (HDD) 514, a magnetic floppy diskdrive (FDD) 516 to read from or write to a removable magnetic disk 518,and an optical disk drive 520 to read from or write to a removableoptical disk 522 (e.g., a CD-ROM or DVD). The HDD 514, FDD 516 andoptical disk drive 520 can be connected to the chipset and bus 508 by aHDD interface 524, an FDD interface 526 and an optical drive interface528, respectively. The HDD interface 524 for external driveimplementations can include at least one or both of Universal Serial Bus(USB) and Institute of Electrical and Electronics Engineers (IEEE) 694interface technologies. In various embodiments, these types of memorymay not be included in main memory or system memory.

The drives and associated computer-readable media provide volatileand/or nonvolatile storage of data, data structures, computer-executableinstructions, and so forth. For example, a number of program modules canbe stored in the drives and memory units 510, 512, including anoperating system 530, one or more application programs 532, otherprogram modules 534, and program data 536. In one embodiment, the one ormore application programs 532, other program modules 534, and programdata 536 can include or implement, for example, the various techniques,applications, and/or components described herein.

A user can enter commands and information into the computer 502 throughone or more wire/wireless input devices, for example, a keyboard 538 anda pointing device, such as a mouse 540. Other input devices may includemicrophones, infra-red (IR) remote controls, radio-frequency (RF) remotecontrols, game pads, stylus pens, card readers, dongles, finger printreaders, gloves, graphics tablets, joysticks, keyboards, retina readers,touch screens (e.g., capacitive, resistive, etc.), trackballs,trackpads, sensors, styluses, and the like. These and other inputdevices are often connected to the processing unit 504 through an inputdevice interface 542 that is coupled to the chipset and bus 508, but canbe connected by other interfaces such as a parallel port, IEEE 994serial port, a game port, a USB port, an IR interface, and so forth.

A monitor 544 or other type of display device is also connected to thechip set and bus 508 via an interface, such as a video adaptor 546 orother display driver. The monitor 544 may be internal or external to thecomputer 502. In addition to the monitor 544, a computer typicallyincludes other peripheral output devices, such as speakers, printers,and so forth.

The computer 502 may operate in a networked environment using logicalconnections via wire and/or wireless communications to one or moreremote computers, such as a remote computer 548. In various embodiments,one or more migrations may occur via the networked environment. Theremote computer 548 can be a workstation, a server computer, a router, apersonal computer, portable computer, microprocessor-based entertainmentappliance, a peer device or other common network node, and typicallyincludes many or all the elements described relative to the computer502, although, for purposes of brevity, only a memory/storage device 550is illustrated. The logical connections depicted include wire/wirelessconnectivity to a local area network (LAN) 552 and/or larger networks,for example, a wide area network (WAN) 554. Such LAN and WAN networkingenvironments are commonplace in offices and companies, and facilitateenterprise-wide computer networks, such as intranets, all of which mayconnect to a global communications network, for example, the Internet.

When used in a LAN networking environment, the computer 502 is connectedto the LAN 552 through a wire and/or wireless communication networkinterface or adaptor 556. The adaptor 556 can facilitate wire and/orwireless communications to the LAN 552, which may also include awireless access point disposed thereon for communicating with thewireless functionality of the adaptor 556.

When used in a WAN networking environment, the computer 502 can includea modem 558, or is connected to a communications server on the WAN 554,or has other means for establishing communications over the WAN 554,such as by way of the Internet. The modem 558, which can be internal orexternal and a wire and/or wireless device, connects to the chipset andbus 508 via the input device interface 542. In a networked environment,program modules depicted relative to the computer 502, or portionsthereof, can be stored in the remote memory/storage device 550. It willbe appreciated that the network connections shown are exemplary andother means of establishing a communications link between the computerscan be used.

The computer 502 is operable to communicate with wire and wirelessdevices or entities using the IEEE 802 family of standards, such aswireless devices operatively disposed in wireless communication (e.g.,IEEE 802.16 over-the-air modulation techniques). This includes at leastWi-Fi (or Wireless Fidelity), WiMax, and Bluetooth™ wirelesstechnologies, among others. Thus, the communication can be a predefinedstructure as with a conventional network or simply an ad hoccommunication between at least two devices. Wi-Fi networks use radiotechnologies called IEEE 802.11x (a, b, g, n, etc.) to provide secure,reliable, fast wireless connectivity. A Wi-Fi network can be used toconnect computers to each other, to the Internet, and to wire networks(which use IEEE 802.3-related media and functions).

FIG. 6 is a block diagram illustrating an exemplary system architecture600 according to one or more embodiments described herein. Inarchitecture 600, client device 602 may be coupled to a data storagedevice 618, a display 608, and/or a server 628. Embodiments are notlimited in this context.

A client device 602 may be a computing device configured to receiveinput including source code, comments, and/or other input. For example,a client device 602 may be a desktop computer, a laptop, a mobiledevice, or other device. In various embodiments, a client device 602 mayinclude and/or be coupled to one or more input devices to enablereception of input, for example, a keyboard, a mouse, a touch screen, orother device. In many embodiments, a client device 602 may include anarchitecture such as architecture 500, discussed with respect to FIG. 5,and/or system 800, discussed with respect to FIG. 8.

A client device 602 may include logic circuitry 604 and an integrateddevelopment environment (IDE) 606. Logic circuitry 604 may includehardware and/or hardware with instructions stored thereon. In someembodiments, an IDE 606 may be included in the logic circuitry 604. AnIDE 606 may include a code editor, a compiler, and/or a GUI enabling auser to write and edit source code. Logic circuitry 604 may beconfigured to manage comments in a source code, for example, a sourcecode received via an IDE 606. For example, logic circuitry 604 may beconfigured to analyze source code. Based on the analysis, the logiccircuitry 604 may generate comments to add to the source code. In someembodiments, the logic circuitry 604 may determine whether a comment ina source code is obsolete. Based on the determination, the logiccircuitry 604 may delete the obsolete comment or generate an alternativecomment. The logic circuitry 604 may be configured to present one ormore recommendations relating to comment management via the IDE 606. Forexample, logic circuitry 604 may be configured to present aspects ofuser interface 101 via a GUI of IDE 606.

In many embodiments, a GUI of an IDE may be presented via a display 608coupled to the client device 602. The display 608 may be a part of thesame or a different device from client device 602. For example, adisplay 608 may be a monitor coupled to a desktop computer, a laptopscreen, or a screen of a mobile device. The display 608 may operate viaa display driver. In many cases, the client device 602 may comprise adisplay driver 610 for the display 608. In some embodiments, a displaydriver 612 may be included in logic circuitry 622 in the display 608.The display 608 may be configured to display pixels associated with eachunique user interface. The display driver 610 and/or display driver 612may store the pixels in memory, such as memory 614 and/or memory 616,respectively, such that each unique user interface corresponds tophysical changes of the memory by the display driver(s). Accordingly,each user interface not presented before may result in a unique physicalconfiguration of the memory.

The memory may be included onboard the client device 602, such as withmemory 614. In some embodiments, memory may be externally coupled to theclient device 602. For example, a data storage device 618 may containmemory 620. In some embodiments, memory may contain and/or be coupled tologic circuitry, such as logic circuitry 604. In some embodiments,memory may contain data relating to at least one user, code source, codedatabank, code language, or other information to enable logic circuitryto manage comments in a code, for example, by the processes describedwith respect to FIG. 4. For example, a memory may include one or morerules or formatting procedures associated with a code language. In someembodiments, memory may include a library 213.

In many embodiments, a client device 602 may be communicatively coupledwith at least one server, such as server 628. One or more aspects of amemory 620 may be stored on and/or accessed via the server 628. Forexample, a memory 620 may include a library 213.

In some embodiments, a display 608, a data storage device 618, and/or aserver 628 may include logic circuitry to implement part of or all ofthe functionality of a comment management system. Accordingly, logiccircuitry 622 on a display 608, logic circuitry 624 on a data storagedevice 618, and/or logic circuitry 626 on a server 628 may operate theprocesses described with respect to FIG. 4. For example, logic of block401 may be implemented by logic circuitry 622. Training logic 402 may belocated on logic circuitry 626, comment identification logic 413 andobsoletion detection logic 418 may be implemented on logic circuitry624, and comment update logic 413 may be implemented on logic 604.

Additionally, it will be understood that more than one client device602, display 608, data storage device 618, and/or server 628 maycoordinate to form a comment management system. For example, multipleservers 628 may correspond to a plurality of sources of code banks, suchas various open-source platforms. Embodiments are not limited in thiscontext.

FIG. 7 illustrates a block diagram of an exemplary communicationsarchitecture 700 suitable for implementing various embodiments aspreviously described, such as virtual machine migration. Thecommunications architecture 700 includes various common communicationselements, such as a transmitter, receiver, transceiver, radio, networkinterface, baseband processor, antenna, amplifiers, filters, powersupplies, and so forth. The embodiments, however, are not limited toimplementation by the communications architecture 700.

As shown in FIG. 7, the communications architecture 700 comprisesincludes one or more clients 702 and servers 704. In some embodiments,communications architecture 700 may include or implement one or moreportions of components, applications, and/or techniques describedherein. For example, a comment manager 204 may be implemented on one ormore clients 702 and/or servers 704. The clients 702 and the servers 704are operatively connected to one or more respective client data stores708 and server data stores 710 that can be employed to store informationlocal to the respective clients 702 and servers 704, such as cookiesand/or associated contextual information. For example, a client datastore 708 and/or a server data store 710 may be a library 213. Invarious embodiments, any one of servers 704 may implement one or more oflogic flows or operations described herein in conjunction with storageof data received from any one of clients 702 on any of server datastores 710. In one or more embodiments, one or more of client datastore(s) 708 or server data store(s) 710 may include memory accessibleto one or more portions of components, applications, and/or techniquesdescribed herein.

The clients 702 and the servers 704 may communicate information betweeneach other using a communication framework 706. The communicationsframework 706 may implement any well-known communications techniques andprotocols. The communications framework 706 may be implemented as apacket-switched network (e.g., public networks such as the Internet,private networks such as an enterprise intranet, and so forth), acircuit-switched network (e.g., the public switched telephone network),or a combination of a packet-switched network and a circuit-switchednetwork (with suitable gateways and translators).

The communications framework 706 may implement various networkinterfaces arranged to accept, communicate, and connect to acommunications network. A network interface may be regarded as aspecialized form of an input output interface. Network interfaces mayemploy connection protocols including without limitation direct connect,Ethernet (e.g., thick, thin, twisted pair 10/100/1900 Base T, and thelike), token ring, wireless network interfaces, cellular networkinterfaces, IEEE 802.11a-x network interfaces, IEEE 802.16 networkinterfaces, IEEE 802.20 network interfaces, and the like. Further,multiple network interfaces may be used to engage with variouscommunications network types. For example, multiple network interfacesmay be employed to allow for the communication over broadcast,multicast, and unicast networks. Should processing requirements dictatea greater amount speed and capacity, distributed network controllerarchitectures may similarly be employed to pool, load balance, andotherwise increase the communicative bandwidth required by clients 702and the servers 704. A communications network may be any one and thecombination of wired and/or wireless networks including withoutlimitation a direct interconnection, a secured custom connection, aprivate network (e.g., an enterprise intranet), a public network (e.g.,the Internet), a Personal Area Network (PAN), a Local Area Network(LAN), a Metropolitan Area Network (MAN), an Operating Missions as Nodeson the Internet (OMNI), a Wide Area Network (WAN), a wireless network, acellular network, and other communications networks.

Various embodiments may be implemented using hardware elements, softwareelements, or a combination of both. Examples of hardware elements mayinclude processors, microprocessors, circuits, circuit elements (e.g.,transistors, resistors, capacitors, inductors, and so forth), integratedcircuits, application specific integrated circuits (ASIC), programmablelogic devices (PLD), digital signal processors (DSP), field programmablegate array (FPGA), logic gates, registers, semiconductor device, chips,microchips, chip sets, and so forth. Examples of software may includesoftware components, programs, applications, computer programs,application programs, system programs, machine programs, operatingsystem software, middleware, firmware, software modules, routines,subroutines, functions, methods, procedures, software interfaces,application program interfaces (API), instruction sets, computing code,computer code, code segments, computer code segments, words, values,symbols, or any combination thereof. Determining whether an embodimentis implemented using hardware elements and/or software elements may varyin accordance with any number of factors, such as desired computationalrate, power levels, heat tolerances, processing cycle budget, input datarates, output data rates, memory resources, data bus speeds and otherdesign or performance constraints.

One or more aspects of at least one embodiment may be implemented byrepresentative instructions stored on a machine-readable medium whichrepresents various logic within the processor, which when read by amachine causes the machine to fabricate logic to perform the techniquesdescribed herein. Such representations, known as “IP cores” may bestored on a tangible, machine readable medium and supplied to varioususers or manufacturing facilities to load into the fabrication machinesthat actually make the logic or processor. Some embodiments may beimplemented, for example, using a machine-readable medium or articlewhich may store an instruction or a set of instructions that, ifexecuted by a machine, may cause the machine to perform a method and/oroperations in accordance with the embodiments. Such a machine mayinclude, for example, any suitable processing platform, computingplatform, computing device, processing device, computing system,processing system, computer, processor, or the like, and may beimplemented using any suitable combination of hardware and/or software.The machine-readable medium or article may include, for example, anysuitable type of memory unit, memory device, memory article, memorymedium, storage device, storage article, storage medium and/or storageunit, for example, memory, removable or non-removable media, erasable ornon-erasable media, writeable or re-writeable media, digital or analogmedia, hard disk, floppy disk, Compact Disk Read Only Memory (CD-ROM),Compact Disk Recordable (CD-R), Compact Disk Rewriteable (CD-RW),optical disk, magnetic media, magneto-optical media, removable memorycards or disks, various types of Digital Versatile Disk (DVD), a tape, acassette, or the like. The instructions may include any suitable type ofcode, such as source code, compiled code, interpreted code, executablecode, static code, dynamic code, encrypted code, and the like,implemented using any suitable high-level, low-level, object-oriented,visual, compiled and/or interpreted programming language.

FIG. 8 illustrates an embodiment of a system 800 such as the client 702in FIG. 7. The system 800 is a computer system with multiple processorcores such as a distributed computing system, supercomputer,high-performance computing system, computing cluster, mainframecomputer, mini-computer, client-server system, personal computer (PC),workstation, server, portable computer, laptop computer, tabletcomputer, handheld device such as a personal digital assistant (PDA), orother device for processing, displaying, or transmitting information.Similar embodiments may comprise, e.g., entertainment devices such as aportable music player or a portable video player, a smart phone or othercellular phone, a telephone, an external storage device, or the like.Further embodiments implement larger scale server configurations. Inother embodiments, the system 800 may have a single processor with onecore or more than one processor. Note that the term “processor” refersto a processor with a single core or a processor package with multipleprocessor cores.

As shown in FIG. 8, system 800 comprises a motherboard 805 for mountingplatform components. The motherboard 805 is a point-to-pointinterconnect platform that includes a first processor 810 and a secondprocessor 830 coupled via a point-to-point interconnect 856 such as anUltra Path Interconnect (UPI). In other embodiments, the system 800 maybe of another bus architecture, such as a multi-drop bus. Furthermore,each of processors 810 and 830 may be processor packages with multipleprocessor cores including processor core(s) 820 and 840, respectively.While the system 800 is an example of a two-socket (2S) platform, otherembodiments may include more than two sockets or one socket. Forexample, some embodiments may include a four-socket (4S) platform or aneight-socket (8S) platform. Each socket is a mount for a processor andmay have a socket identifier. Note that the term platform refers to themotherboard with certain components mounted such as the processors 810and the chipset 860. Some platforms may include additional componentsand some platforms may only include sockets to mount the processorsand/or the chipset.

In some embodiments, the processor core(s) 820 and 842 may comprisecomment management logic circuitry such as that described with respectto FIG. 2. The comment management logic circuitry may include logiccircuitry configured to perform the operations described in conjunctionwith FIG. 4.

The first processor 810 includes an integrated memory controller (IMC)814 and point-to-point (P-P) interfaces 818 and 852. Similarly, thesecond processor 830 includes an IMC 834 and P-P interfaces 838 and 854.The IMC's 814 and 834 couple the processors 810 and 830, respectively,to respective memories, a memory 812 and a memory 832. The memories 812and 832 may be portions of the main memory (e.g., a dynamicrandom-access memory (DRAM)) for the platform (such as in data storagedevice 618 in FIG. 6) such as double data rate type 3 (DDR3) or type 4(DDR4) synchronous DRAM (SDRAM). In the present embodiment, the memories812 and 832 locally attach to the respective processors 810 and 830. Inother embodiments, the main memory may couple with the processors via abus and shared memory hub.

The processors 810 and 830 comprise caches coupled with each of theprocessor core(s) 820 and 840, respectively. In some embodiments, theprocessors 810 and 830 may be respectively coupled with registers 816and 836. The first processor 810 couples to a chipset 860 via P-Pinterconnects 852 and 862 and the second processor 830 couples to achipset 860 via P-P interconnects 854 and 864. Direct Media Interfaces(DMIs) 857 and 858 may couple the P-P interconnects 852 and 862 and theP-P interconnects 854 and 864, respectively. The DMI may be a high-speedinterconnect that facilitates, e.g., eight Giga Transfers per second(GT/s) such as DMI 3.0. In other embodiments, the processors 810 and 830may interconnect via a bus.

The chipset 860 may comprise a controller hub such as a platformcontroller hub (PCH). The chipset 860 may include a system clock toperform clocking functions and include interfaces for an I/O bus such asa universal serial bus (USB), peripheral component interconnects (PCIs),serial peripheral interconnects (SPIs), integrated interconnects (I2Cs),and the like, to facilitate connection of peripheral devices on theplatform. In other embodiments, the chipset 860 may comprise more thanone controller hub such as a chipset with a memory controller hub, agraphics controller hub, and an input/output (I/O) controller hub.

In the present embodiment, the chipset 860 couples with a trustedplatform module (TPM) 872 and the Unified Extensible Firmware Interface(UEFI), BIOS, Flash component 874 via an interface (I/F) 870. The TPM872 is a dedicated microcontroller designed to secure hardware byintegrating cryptographic keys into devices. The UEFI, BIOS, Flashcomponent 874 may provide pre-boot code.

Furthermore, chipset 860 includes an I/F 866 to couple chipset 860 witha high-performance graphics engine, graphics card 865 and a host fabricinterface (HFI) 867. The I/F 866 may be, for example, a PeripheralComponent Interconnect-enhanced (PCI-e). The HFI 867 may include anetwork interface to couple the system 800 with a connectivity fabric.The HFI 867 may be a network interface card (NIC) coupled with thesystem 800 or may comprise a portion of an integrated circuit of thechipset 860 or of a processor such as the processor 810 and/or theprocessor 830. The HFI 867 may interface the system 800 with othersystems or storage devices via a connectivity fabric such as FibreChannel or the like.

Various I/O devices 892 may couple to the bus 881, along with a busbridge 880 which couples the bus 881 to a second bus 891 and an I/F 868that connects the bus 881 with the chipset 860. In one embodiment, thesecond bus 891 may be a low pin count (LPC) bus. Various devices maycouple to the second bus 891 including, for example, a keyboard 882, amouse 884, communication devices 886, and a data storage unit 888 thatmay store code. Furthermore, an audio I/O 890 may couple to second bus891. Many of the I/O devices 892, the communication devices 886, and thedata storage unit 888 may reside on the motherboard 805 while thekeyboard 882 and the mouse 884 may be add-on peripherals. In otherembodiments, some or all the I/O devices 892, communication devices 886,and the data storage unit 888 are add-on peripherals and do not resideon the motherboard 805. In some embodiments, the data storage unit 888may comprise a comment management executable 894 that can execute of aprocessor core such as the processor core(s) 820 and 840 to configurecomment management logic circuitry 822 and/or 842.

FIG. 9 illustrates an example of a storage medium 900 to store processordata structures. Storage medium 900 may comprise an article ofmanufacture. In some examples, storage medium 900 may include anynon-transitory computer readable medium or machine-readable medium, suchas an optical, magnetic or semiconductor storage. Storage medium 900 maystore diverse types of computer executable instructions, such asinstructions to implement logic flows and/or techniques describedherein. Examples of a computer readable or machine-readable storagemedium may include any tangible media capable of storing electronicdata, including volatile memory or non-volatile memory, removable ornon-removable memory, erasable or non-erasable memory, writeable orre-writeable memory, and so forth. Examples of computer executableinstructions may include any suitable type of code, such as source code,compiled code, interpreted code, executable code, static code, dynamiccode, object-oriented code, visual code, and the like.

FIG. 10 illustrates an example computing platform 1000 such as thedevice of computing architecture 500 in FIG. 5, client 702 in FIG. 7,system 800 in FIG. 8. In some examples, as shown in FIG. 9, computingplatform 1000 may include a processing component 1010, other platformcomponents or a communications interface 1030. According to someexamples, computing platform 1000 may be a computing device such as aserver in a system such as a data center or server farm that supports amanager or controller for managing configurable computing resources asmentioned above. Furthermore, the communications interface 1030 maycomprise a wake-up radio (WUR) and may be capable of waking up a mainradio of the computing platform 1000.

According to some examples, processing component 1010 may executeprocessing operations or logic for apparatus 1015 described herein.Processing component 1010 may include various hardware elements,software elements, or a combination of both. Examples of hardwareelements may include devices, logic devices, components, processors,microprocessors, circuits, processor circuits, circuit elements (e.g.,transistors, resistors, capacitors, inductors, and so forth), integratedcircuits, application specific integrated circuits (ASIC), programmablelogic devices (PLD), digital signal processors (DSP), field programmablegate array (FPGA), memory units, logic gates, registers, semiconductordevice, chips, microchips, chip sets, and so forth. Examples of softwareelements, which may reside in the storage medium 1020, may includesoftware components, programs, applications, computer programs,application programs, device drivers, system programs, softwaredevelopment programs, machine programs, operating system software,middleware, firmware, software modules, routines, subroutines,functions, methods, procedures, software interfaces, application programinterfaces (API), instruction sets, computing code, computer code, codesegments, computer code segments, words, values, symbols, or anycombination thereof. In some embodiments, a storage medium 1020 may haveone or more aspects in common with a storage medium 900. Whilediscussions herein describe elements of embodiments as software elementsand/or hardware elements, decisions to implement an embodiment usinghardware elements and/or software elements may vary in accordance withany number of design considerations or factors, such as desiredcomputational rate, power levels, heat tolerances, processing cyclebudget, input data rates, output data rates, memory resources, data busspeeds and other design or performance constraints.

In some examples, other platform components 1025 may include commoncomputing elements, such as one or more processors, multi-coreprocessors, co-processors, memory units, chipsets, controllers,peripherals, interfaces, oscillators, timing devices, video cards, audiocards, multimedia input/output (I/O) components (e.g., digitaldisplays), power supplies, and so forth. Examples of memory units mayinclude without limitation various types of computer readable andmachine readable storage media in the form of one or more higher speedmemory units, such as read-only memory (ROM), random-access memory(RAM), dynamic RAM (DRAM), Double-Data-Rate DRAM (DDRAM), synchronousDRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasableprogrammable ROM (EPROM), electrically erasable programmable ROM(EEPROM), flash memory, polymer memory such as ferroelectric polymermemory, ovonic memory, phase change or ferroelectric memory,silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic or opticalcards, an array of devices such as Redundant Array of Independent Disks(RAID) drives, solid state memory devices (e.g., USB memory), solidstate drives (SSD) and any other type of storage media suitable forstoring information.

In some examples, communications interface 1030 may include logic and/orfeatures to support a communication interface. For these examples,communications interface 1030 may include one or more communicationinterfaces that operate according to various communication protocols orstandards to communicate over direct or network communication links.Direct communications may occur via use of communication protocols orstandards described in one or more industry standards (includingprogenies and variants) such as those associated with the PCI Expressspecification. Network communications may occur via use of communicationprotocols or standards such as those described in one or more Ethernetstandards promulgated by the Institute of Electrical and ElectronicsEngineers (IEEE). For example, one such Ethernet standard may includeIEEE 802.3-2012, Carrier sense Multiple access with Collision Detection(CSMA/CD) Access Method and Physical Layer Specifications, Published inDecember 2012 (hereinafter “IEEE 802.3”). Network communication may alsooccur according to one or more OpenFlow specifications such as theOpenFlow Hardware Abstraction API Specification. Network communicationsmay also occur according to Infiniband Architecture Specification,Volume 1, Release 1.3, published in March 2015 (“the InfinibandArchitecture specification”).

Computing platform 1000 may be part of a computing device that may be,for example, a server, a server array or server farm, a web server, anetwork server, an Internet server, a work station, a mini-computer, amain frame computer, a supercomputer, a network appliance, a webappliance, a distributed computing system, multiprocessor systems,processor-based systems, or combination thereof. Accordingly, variousembodiments of the computing platform 1000 may include or excludefunctions and/or specific configurations of the computing platform 1000described herein.

The components and features of computing platform 1000 may comprise anycombination of discrete circuitry, ASICs, logic gates and/or single chiparchitectures. Further, the features of computing platform 1000 maycomprise microcontrollers, programmable logic arrays and/ormicroprocessors or any combination of the foregoing where suitablyappropriate. Note that hardware, firmware and/or software elements maybe collectively or individually referred to herein as “logic”.

One or more aspects of at least one example may comprise representativeinstructions stored on at least one machine-readable medium whichrepresents various logic within the processor, which when read by amachine, computing device or system causes the machine, computing deviceor system to fabricate logic to perform the techniques described herein.Such representations, known as “IP cores” may be stored on a tangible,machine readable medium and supplied to various customers ormanufacturing facilities to load into the fabrication machines that makethe logic or processor.

Some examples may include an article of manufacture or at least onecomputer-readable medium. A computer-readable medium may include anon-transitory storage medium to store logic. In some examples, thenon-transitory storage medium may include one or more types ofcomputer-readable storage media capable of storing electronic data,including volatile memory or non-volatile memory, removable ornon-removable memory, erasable or non-erasable memory, writeable orre-writeable memory, and so forth. In some examples, the logic mayinclude various software elements, such as software components,programs, applications, computer programs, application programs, systemprograms, machine programs, operating system software, middleware,firmware, software modules, routines, subroutines, functions, methods,procedures, software interfaces, API, instruction sets, computing code,computer code, code segments, computer code segments, words, values,symbols, or any combination thereof.

According to some examples, a computer-readable medium may include anon-transitory storage medium to store or maintain instructions thatwhen executed by a machine, computing device or system, cause themachine, computing device or system to perform methods and/or operationsin accordance with the described examples. The instructions may includeany suitable type of code, such as source code, compiled code,interpreted code, executable code, static code, dynamic code, and thelike. The instructions may be implemented according to a predefinedcomputer language, manner, or syntax, for instructing a machine,computing device or system to perform a certain function. Theinstructions may be implemented using any suitable high-level,low-level, object-oriented, visual, compiled and/or interpretedprogramming language.

As used herein, the term “circuitry” may refer to, be part of, orinclude an Application Specific Integrated Circuit (ASIC), an electroniccircuit, a processor (shared, dedicated, or group), and/or memory(shared, dedicated, or group) that execute one or more software orfirmware programs, a combinational logic circuit, and/or other suitablehardware components that provide the described functionality.

Various examples may be implemented using hardware elements, softwareelements, or a combination of both. In some examples, hardware elementsmay include devices, components, processors, microprocessors, circuits,circuit elements (e.g., transistors, resistors, capacitors, inductors,and so forth), integrated circuits, application specific integratedcircuits (ASIC), programmable logic devices (PLD), digital signalprocessors (DSP), field programmable gate array (FPGA), memory units,logic gates, registers, semiconductor device, chips, microchips, chipsets, and so forth. In some examples, software elements may includesoftware components, programs, applications, computer programs,application programs, system programs, machine programs, operatingsystem software, middleware, firmware, software modules, routines,subroutines, functions, methods, procedures, software interfaces,application program interfaces (API), instruction sets, computing code,computer code, code segments, computer code segments, words, values,symbols, or any combination thereof. Determining whether an example isimplemented using hardware elements and/or software elements may vary inaccordance with any number of factors, such as desired computationalrate, power levels, heat tolerances, processing cycle budget, input datarates, output data rates, memory resources, data bus speeds and otherdesign or performance constraints, as desired for a givenimplementation.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code to reduce the number of times code must be retrievedfrom bulk storage during execution. The term “code” covers a broad rangeof software components and constructs, including applications, drivers,processes, routines, methods, modules, firmware, microcode, andsubprograms. Thus, the term “code” may be used to refer to anycollection of instructions which, when executed by a processing system,perform a desired operation or operations.

Processing circuitry, logic circuitry, devices, and interfaces hereindescribed may perform functions and/or store code and/or data to performfunctions to implement entirely in hardware and/or entirely or partiallywith code executed on one or more processors. Processing circuitry, orlogic circuitry, refers to the hardware or the hardware and code thatimplements one or more logical functions. Circuitry is hardware and mayrefer to one or more circuits. Each circuit may perform a particularfunction. A circuit of the circuitry may comprise discrete electricalcomponents interconnected with one or more conductors, an integratedcircuit, a chip package, a chip set, memory, or the like. Integratedcircuits include circuits created on a substrate such as a silicon waferand may comprise components. And integrated circuits, processorpackages, chip packages, and chipsets may comprise one or moreprocessors.

Processors may receive signals such as instructions and/or data at theinput(s) and process the signals to generate the at least one output.While executing code, the code changes the physical states andcharacteristics of transistors that make up a processor pipeline. Thephysical states of the transistors translate into logical bits of onesand zeros stored in registers within the processor. The processor cantransfer the physical states of the transistors into registers andtransfer the physical states of the transistors to another storagemedium.

A processor may comprise circuits or circuitry to perform one or moresub-functions implemented to perform the overall function of theprocessor. One example of a processor is a state machine or anapplication-specific integrated circuit (ASIC) that includes at leastone input and at least one output. A state machine may manipulate the atleast one input to generate the at least one output by performing apredetermined series of serial and/or parallel manipulations ortransformations on the at least one input.

What is claimed is:
 1. An apparatus comprising: memory; and logiccircuitry coupled with the memory to identify a program code segmentwith an associated comment; generate an intermediate code segment basedon the program code segment, the intermediate code segment comprisingcode at an intermediate stage of compilation between program code andcompiled code; identify a library code segment corresponding to theintermediate code segment; identify a set of one or more comments basedon an association between the library code segment and the set of one ormore comments; compare the associated comment with the set of one ormore comments to determine that a deviation between the associatedcomment and the set of one or more comments exceeds a deviationthreshold; and output an indication that the associated comment might beobsolete.
 2. The apparatus of claim 1, the logic circuitry to receive aselection of the program segment and a request to determine whether theassociated comment might be obsolete.
 3. The apparatus of claim 1, thelogic circuitry to detect an edit of the program segment, the detectionto identify the program segment.
 4. The apparatus of claim 1, the logiccircuitry to generate the intermediate code segment by compilation ofthe program code segment to the intermediate stage of compilation. 5.The apparatus of claim 1, the logic circuitry to compare theintermediate code segment to the library code segment to identify thelibrary code segment.
 6. The apparatus of claim 1, the logic circuitryto implement a model, the model to identify the library code segmentbased on the intermediate code segment.
 7. The apparatus of claim 6,wherein the model comprises a database, a statistical model, a machinelearning model, or a combination thereof.
 8. The apparatus of claim 7,the model to compare the associated comment with the set of one or morecomments to determine the deviation based on a lack of an exact match.9. The apparatus of claim 7, the statistical model to determineLevenshtein distance metrics based on the associated comment and the setof one or more comments to determine the deviation.
 10. The apparatus ofclaim 7, the machine learning model to perform natural languageprocessing based on the associated comment and the set of one or morecomments to determine the deviation.
 11. A non-transitory storage mediumcontaining instructions, which when executed by a processor, cause theprocessor to perform operations, the operations to: identify a programcode segment with an associated comment; generate an intermediate codesegment based on the program code segment, the intermediate code segmentcomprising code at an intermediate stage of compilation between programcode and compiled code; identify a library code segment corresponding tothe intermediate code segment; identify a set of one or more commentsbased on an association between the library code segment and the set ofone or more comments; compare the associated comment with the set of oneor more comments to determine that a deviation between the associatedcomment and the set of one or more comments exceeds a deviationthreshold; and output an indication that the associated comment might beobsolete.
 12. The non-transitory storage medium of claim 11, theoperations to receive an indication of a request to determine whetherthe associated comment for the program code segment might be obsolete.13. The non-transitory storage medium of claim 11, wherein theoperations generate the intermediate code segment by compilation of theprogram code segment to the intermediate stage of compilation.
 14. Thenon-transitory storage medium of claim 11, wherein the operationsidentify the library code segment by comparison of the intermediate codesegment to the library code segment.
 15. The non-transitory storagemedium of claim 11, wherein the operations implement a model, the modelto identify the library code segment based on the intermediate codesegment.
 16. The non-transitory storage medium of claim 15, wherein themodel comprises a database, a statistical model, a machine learningmodel, or a combination thereof.
 17. The non-transitory storage mediumof claim 16, the model to compare the associated comment with the set ofone or more comments to determine the deviation based on a lack of anexact match.
 18. The non-transitory storage medium of claim 17, themachine learning model to perform natural language processing based onthe associated comment and the set of one or more comments to determinethe deviation.
 19. The non-transitory storage medium of claim 16, thestatistical model to determine Levenshtein distance metrics based on theassociated comment and the set of one or more comments to determine thedeviation.
 20. A system comprising: memory; and logic circuitry coupledwith the memory to identify multiple, different program codes; parse themultiple, different program codes into training program segments, eachof the training program segments to include an associated comment;compile each of the training program segments to generate correspondingintermediate code segments, each of the intermediate code segmentsassociated with a corresponding training code segment and the associatedcomment of the corresponding training code segment, wherein theintermediate code segments include repetitions, the repetitionsassociated with differing associated comments; and train a machinelearning model to determine a probability based on an input intermediatecode segment and an input comment, the probability to indicate alikelihood that the input comment matches the input intermediate codesegment.